The monthly means of NCEP/NCAR Reanalysis (R1) products, archived in ds090.0 dataset, are extracted and reorganized into subgroups in this dataset. The groupings try to combine like and/or commonly used parameter-level data together. There are also subgroups for each of the four diurnal monthly means (means of 00Z, 06Z, 12Z, and 18Z separately).

The data files are in WMO GRIB format. Both the monthly means and their variances are in the same file but in different GRIB records. Examples of separating monthly means from variances are shown in this guide.

All subgroups will be available on line under data. The ones that are not on line yet will be moved over upon request.

ABSTRACT Y-rank can present faults when dealing with non-linear problems. A methodology is proposed to improve the selection of data in situations where y-rank is fragile. The proposed alternative, called k-rank, consists of splitting the data set into clusters using the k-means algorithm, and then apply y-rank to the generated clusters. Models were calibrated and tested with subsets split by y-rank and k-rank. For the Heating Tank case study, in 59% of the simulations, models calibrated with k-rank subsets achieved better results. For the Propylene / Propane Separation Unit case, when dealing with a small number of sample points, the y-rank models had errors almost three times higher than the k-rank models for the test subset, meaning that the fitted model could not deal properly with new unseen data. The proposed methodology was successful in splitting the data, especially in cases with a limited amount of samples.

Eurostat data contains many indicators (short-term, structural, theme-specific and others) on the EU-28 and the Eurozone, the Member States and their partners. The database of Eurostat contains always the latest version of the datasets meaning that there is no versioning on the data. Datasets are updated twice a day, at 11:00 and at 23:00, in case new data is available or because of structural change. It is possible to access the datasets through SDMX Web Services, as well as through Json and Unicode Web Services. SDMX Web Services are a programmatic access to Eurostat data, with the possibility to: get a complete list of publicly available datasets; detail the complete structure definition of a given dataset; download a subset of a given dataset or a full dataset. SDMX Web Services: provide access to datasets listed under database by themes, and predefined tables listed under tables by themes; provide data in SDMX 2.0 and 2.1 formats; support both Representation State Transfer (REST) and Simple Object Access Protocol (SOAP) protocols; return responses in English language only; are free of charge. The JSON & UNICODE Web Services are a programmatic access to Eurostat data, with the possibility to download a subset of a given dataset. This operation allows customizing requests for data. You can filter on dimensions to retrieve specific data subsets. The JSON & UNICODE Web Services: provide data in JSON-stat and UNICODE formats; support only Representation State Transfer (REST) protocol; deliver responses in English, French and German language; are free of charge.

This repository stores the raw data that gave rise to the study by Mombelli et al. (2024) (Title: Auditory stimuli suppress contextual fear responses in safety learning independent of a possible safety meaning; DOI: 10.3389/fnbeh.2024.1415047, Journal: Frontiers in Behavioral Neuroscience). Below we supply information on the provided metadata files which, in turn, refer to individual raw data files.

General structure of the repository:

· the raw data is organized in 5 subsets defined by the figures or supplementary figures they contribute to. Each subset is documented by its own metadata file. Raw data files were compressed into ZIP archives, one per subset;

· the metadata files listing names of the individual data files are provided in “.csv” format, one per data subset. Field separator: comma;

· the dataset is accessible at the following doi: 10.5281/zenodo.13524007

Description of the non-textual data formats:

· video recordings of animal behavior were provided as unmodified ".wmv" files created by the VideoFreeze acquisition software (Med Associates Inc). Video stream parameters: wmv3 codec, color space yuv420p, 320x240 pixels, 30 fps, bitrate 300 kb/s.

· movement traces were obtained from the videos, as described in the Methods section (Mombelli et al., 2024).

17 tables and two figures of this paper. Table 1 is a subset of explicit entries identified in NHANES demographics data. Table 2 is a subset of implicit entries identified in NHANES demographics data. Table 3 is a subset of NHANES demographic Codebook entries. Table 4 presents a subset of explicit entries identified in SEER. Table 5 is a subset of Dictionary Mapping for the MIMIC-III Admission table. Table 6 shows high-level comparison of semantic data dictionaries, traditional data dictionaries, approaches involving mapping languages, and general data integration tools. Table A1 shows namespace prefixes and IRIs for relevant ontologies. Table B1 shows infosheet specification. Table B2 shows infosheet metadata supplement. Table B3 shows dictionary mapping specification. Table B4 is a codebook specification. Table B5 is a timeline specification. Table B6 is properties specification. Table C1 shows NHANES demographics infosheet. Table C2 shows NHANES demographic implicit entries. Table C3 shows NHANES demographic explicit entries. Table C4 presents expanded NHANES demographic Codebook entries. Figure 1 is a conceptual diagram of the Dictionary Mapping that allows for a representation model that aligns with existing scientific ontologies. The Dictionary Mapping is used to create a semantic representation of data columns. Each box, along with the “Relation” label, corresponds to a column in the Dictionary Mapping table. Blue rounded boxes correspond to columns that contain resource URIs, while white boxes refer to entities that are generated on a per-row/column basis. The actual cell value in concrete columns is, if there is no Codebook for the column, mapped to the “has value” object of the column object, which is generally either an attribute or an entity. Figure 2 presents (a) A conceptual diagram of the Codebook, which can be used to assign ontology classes to categorical concepts. Unlike other mapping approaches, the use of the Codebook allows for the annotation of cell values, rather than just columns. (b) A conceptual diagram of the Timeline, which can be used to represent complex time associated concepts, such as time intervals.

Samples of 0.001 and 0.01%, for the smaller iris and miRNA data sets of 1% and 10%, of the data were drawn once using uniform sampling or 1,000 times using uniform sampling with different seeds, followed by selection of the sample that best matched the original distribution of variables, judged by statistical comparisons of probability density functions. The sampled data were subjected to projection using either PCA or a single-layer autoencoder, and then the projection parameters were used to predict the remaining data that had not been sampled from the original data set. The experiments were performed in 20 replicates starting with different and non-redundant seeds, and the means and standard deviations of the mean square errors of the data reproduction obtained during these replicates are shown.

Subset of ERA5 reanalysis on the surface (single-levels) for atmospheric, ocean-wave and land surface quantities. The dataset is provided in a ARCO Zarr format ideal for time series analysis

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: A Housing Unit is defined as any premises or enclosure structurally separate and independent, that has been built or adapted, in whole or in part for purposes of permanent or temporary accommodation of people; as well as any other type of fixed or mobile Housing Unit occupied as a place of residence at 12pm on September 14th. "Separate" will be understood to mean having its own boundaries formed by walls, ceilings, etc. "Independent" will be understood to mean having an entrance or direct access from the street, hallway, stairwell, patio, etc., meaning that in order to enter or exit it is not necessary to pass through the interior of another home. - Households: A census household is the person or group of people, with or without familial ties, who have a common budget, cook for the whole and live together on a regular basis, occupying a housing unit or a part of one. - Group quarters: Housing used as a place of special, temporary or permanent lodging, usually by a group of people without familial connections that generally live together for reasons of convenience, health, work, education, military discipline, religion or other reasons, having to comply with certain cohabitation standards.

Universe

The Population and Housing Census will encompass the Cuban archipelago consisting of the Island of Cuba, Isla de la Juventud, and other adjacent islands and cays that constitute the national territoritories, excluding the Guantanamo naval base.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Office of Statistics of the Republic of Cuba

SAMPLE SIZE (person records): 1115643.

SAMPLE DESIGN: Systematic sample of every 10th household with a random start; drawn by IPUMS.

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form with sections on houesholds and persons

Subset Data 3: 2700 Thoracolumbar Osteo-Ligamentous Spine Virtual FE Meshes (Models 5401 to 8100) 2700 FE input files representing thoracolumbar spine hexahedral models, including point coordinates. To reduce the size of shared virtual finite element (FE) models, only point coordinates are shared here. The mean FE input file "Mean_Model (Template).inp" is also shared, which includes point coordinates, mesh connectivity IDs, and element sets. To generate virtual FE input files, the corresponding shared point coordinates can be replaced into the mean FE input file (Mean_Model (Template).inp). Mesh connectivity IDs, and element sets are the same in all of FE input files. Mean FE input file includes vertebras and IVDs hexahedral meshes; pelvis, sacrum, and the femoral head triangulated meshes; and ligaments. Each point coordinate file is almost 38MB. An excel file: "Descriptive_List (16807_FE_virtual_models).xlsx" reporting measured spinopelvic parameters for virtual FE hexahedral models. The Excel file includes measured spinopelvic parameters (PI, PT, SS, LL, LL-PI, GT, RPV, RLL, LDI, RSA, TPA, and scoliosis cobb angle), GAP and IVD centric thickness for FE virtual cohort. Model ID in the excel file is correspondent to the model’s name. One video file: "how_to_replace_point_coordinates.mp4". It shows how you can replace point coordinates here to the mean FE input file "Mean_Model (Template).inp" in order to generate specific FE input file. Notes: 1- Model number in "Descriptive_List (16807_FE_virtual_models).xlsx" is correspondent to the same model number in the 16807 stereolithography (stl) files (.stl extension) representing the virtual thoracolumbar spine triangulated meshes (DOI: 10.5281/zenodo.8108354; stl.part01.rar to stl.part09.rar). 2-These point coordinates are sampled by combining the first 5 shape modes of the morphed-mesh statistical shape model in which each shape mode is discretized into 7 standard deviations: -3, -2, -1, 0, 1, 2, 3. 3- Generated FE inp files can be opened by Abaqus 2019 and later. Any other FE software which supports .inp extension also can open the files. Developed by: Morteza Rasouligandomani (Ph.D. in biomedical engineering, Pompeu Fabra university, BCN Med-Tech group, DTIC department, Barcelona, Spain). Email contact: morteza.rasouli@upf.edu

We study the behaviour and cognition of wild apes and other species (elephants, corvids, dogs). Our video archive is called the Great Ape Dictionary, you can find out more here www.greatapedictionary.com or about our lab group here www.wildminds.ac.uk We consider these videos to be a data ark that we would like to make as accessible as possible. While we are unable to make the original video files open access at the present time you can search this database to explore what is available, and then request access for collaborations of different kinds by contacting us directly or through our website. We label all videos in the Great Ape Dictionary video archive with basic meta-data on the location, date, duration, individuals present, and behaviour present. Version 1.0.0 contains current data from the Budongo East African chimpanzee population (n=13806 videos). These datasets are being updated regularly and new data will be incorporated here with versioning. As well as the database there is a second read.me file which contains the ethograms used for each variable coded, and a short summary of other datasets that are in preparation for subsequent version(s). If you are interested in these data please contact us. Please note that not all variables are labeled for all videos, the detailed Ethogram categories are only available for a subset of data. All videos are labelled with up to 5 Contexts (at least one, rarely 5). If you are interested in finding a good example video for a particular behaviour, search for 'Library' = Y, this indicates that this clip contains a very clear example of the behaviour.

ABSTRACT: This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format. Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/cramer_lmns_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.

This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10° N to 25° S, longitude 30° to 85° W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format.

Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).

More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/crame….

LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.

tabase is a major update of the Leemans and Cramer database (Leemans and Cramer 1991). It contains long-term monthly averages, for the period 1931-1960, of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5-degree longitude/latitude resolution. It was generated from a larger database, using the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). The current version is 2.1--this is the same version that is currently used widely around the globe, notably by all groups participating in the IGBP NPP model intercomparison.More information can be found at: ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/README.

jats:titleAbstract/jats:titlejats:pRepresentative subsets of global climate models (GCMs) are often used in climate change impact studies to account for uncertainty in ensemble climate projections. However, the effectiveness of such subsets has seldom been assessed for the estimations of either the mean or the spread of the full ensembles. We assessed two different approaches that were employed to select 5 GCMs from a 20-member ensemble of GCMs from the CMIP5 ensemble for projecting canola and spring wheat yields across Canada under RCP 4.5 and 8.5 emission scenarios in the periods 2040–2069 and 2070–2099, based on crop simulation models. Averages and spreads of the simulated crop yields using the 5-GCM subsets selected by T&P and KKZ approaches were compared with the full 20-GCM ensemble. Our results showed that the 5-GCM subsets selected by the two approaches could produce full-ensemble means with a relative absolute error of 2.9–4.7% for canola and 1.5–2.2% for spring wheat, and covers 61.8–91.1% and 66.1–80.8% of the full-ensemble spread for canola and spring wheat, respectively. Our results also demonstrated that both approaches were very likely to outperform a subset of randomly selected 5 GCMs in terms of a smaller error and a larger range./jats:p

These data include a subset of the CMIP6 input data assessed by the IPCC AR6 WGI authors for region North America (170°W - 45°W, 5°N - 85°N). Included is the monthly mean specific humidity (huss) data of the experiments historical, ssp126, ssp245, ssp370, and ssp585 for models providing more than 5 out of 12 core variables.

Further details are provided in the additional information "IPCC AR6 Data for Regions".

These data include a subset of the CMIP6 input data assessed by the IPCC AR6 WGI authors for region Africa (35°W - 72°E, 58°S - 40°N). Included is the monthly mean specific humidity (huss) data of the experiments historical, ssp126, ssp245, ssp370, and ssp585 for models providing more than 5 out of 12 core variables.

Further details are provided in the additional information "IPCC AR6 Data for Regions".

Participant characteristics (mean and standard deviation).

This data set is a subset of a 0.5-degree gridded temperature and precipitation data set for South America (Willmott and Webber 1998). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), defined as 10° N to 25° S, 30° to 85° W. The data are in ASCII GRID format. The data consist of the following: Monthly mean air temperature time series (1960-1990), in degrees C: monthly mean air temperatures for 1960-1990 cross validation errors associated with time series monthly mean air temperatures for 1960-1990, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation time series Monthly mean air temperature climatology, in degrees C: climatic means of monthly and annual air temperatures cross validation errors associated with climatic means climatic means of monthly and annual mean air temperatures, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation climatic means Monthly total precipitation time series (1960-1990), in millimeters: monthly precipitation totals for 1960-1990 cross validation errors associated with time series monthly precipitation totals for 1960-1990, climatologically aided interpolation cross validation errors associated with climatologically aided interpolation time series Monthly total precipitation climatology, in millimeters: climatic means of monthly and annual precipitation totals cross validation errors associated with climatic means More information about the full data set can be found at "Willmott, Matsuura, and Collaborators' Global Climate Resource Pages" (http://climate.geog.udel.edu/~climate) at the University of Delaware. To obtain the original documentation and data, follow the link for "Available Climate Data," register or sign in, and follow the link for "South American Climate Data." Information on the LBA subset can be found at ftp://daac.ornl.gov/data/lba/physical_climate/willmott/comp/willmott_readme.pdf.

This product was developed as part of the project supported by the grant from and the National Oceanic and Atmospheric Administration’s Ocean Acidification Program under award NA18OAR0170430 to the Virginia Institute of Marine Science. The data product consists of water quality data for tidal 98 stations for 1984–2018. The source data used to generate this product were downloaded from the Chesapeake Bay Program’s (CBP) data hub. Out of the total of 255 monitoring stations in the Tidal Monitoring Program, we selected 98 with the long monitoring record (30 years or longer). The following variables were downloaded from the data hub at the native temporal and vertical resolution (between one and four cruises per month and approximately 10 depth levels sampled between 0 and 37 m) for 1984–2018: water temperature (T), salinity (S), pH, total alkalinity (TA), dissolved oxygen (DO) , and chlorophyll (Chl). All pH data prior to 1998 were removed because of the data quality concerns (Herrmann et al., 2020). Briefly, we found a dramatic difference in long-term trends between stations measured by institutions in the state of Virginia and stations measured by the state of Maryland, particularly from late spring to early fall. The boundary between the station groups runs east–west within the mesohaline portion of the bay, where the Potomac River estuary intersects the mainstem bay. The boundary separates strong negative linear trends to the south (Virginia stations) from neutral and weakly positive linear trends to the north (Maryland stations). For all variables, data entries marked with CBP’s “Problem†and “Qualifier†flags were removed. Additionally, all variables were scanned for extreme outliers: for each variable, data from all stations, depths, and times were combined into a single composite sample for which the 75th and 25th percentiles (i.e., the upper and lower quantiles) and the interquartile range (the difference between the upper and lower quantiles) were calculated. Extreme outliers were defined as the values falling outside of a certain number (censoring criterion) of interquartile ranges from the upper and lower quantiles.

Analysis unit

Persons and households Excludes 3 provinces

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: A housing unit means a building or a part of building which is meant for residence of household. It is separate from other parts inside the building from construction and residential point of view. There could be one or more than one housing units/dwelling units in one building, and at the time of enumeration more than one household can reside in one housing unit. - Households: A household means one or more than one person who lives under one cooking arrangement and other common necessities of life. If one person is living alone, he will also be treated as one household. Generally, the members of household are relatives, but the friends, servants of the household and other non relatives residing with them can also be included in the household. - Group quarters: Housing unit which has been constructed or specified as the collective residence of some social, governmental or business purpose, e.g. hotel, hostel, residential, barracks of armed or semi armed forces, residential camps, jails, sanatorium, mental hospital disabled, poor, orphans paupers and institutions etc specified for residence at other such persons.

Universe

All those persons who reside in Pakistan, Azad Jammu and Kashmir and Northern areas and within the boundaries of tribal areas, including Afghans refugees mixing up and living with general population out of camps.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Population Census Organization

SAMPLE SIZE (person records): 13102024.

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the IPUMS. *NOTE: The sample excludes 3 provinces: Fata, Northern Areas, and Kashmir.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two Population Census forms. The short form includes information about household characteristics, basic demographic information about persons in the household and additional information about religion, language, literacy and citizenship. The long form was collected for approximately 8% of the population and included additional questions about migration, disability, occupation, disability and fertility.

This data set is a subset of the global mean monthly climatology (Cramer and Leemans 1999). The subset is for the area of southern Africa within the following bounds: 5 N to 35 S and 5 E to 60 E. The data are available in ASCII grid and binary image formats. The parent database is a major update of the Leemans and Cramer database (Leemans and Cramer 1991). It contains long-term monthly averages, for the period 1931-1960, of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5-degree longitude/latitude resolution. It was generated from a larger database, using the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). The current version is 2.1--this is the same version that is currently used widely around the globe, notably by all groups participating in the IGBP NPP model intercomparison. More information can be found at: ftp://daac.ornl.gov/data/safari2k/climate_meteorology/cramer_leemans/comp/cramer_leemans_readme.pdf.